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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteGartner’s ten strategic IoT technology trends were a forecast for the five-year period from 2018 through 2023—not a current list of technologies expected to emerge over the next five years. The trends covered the whole IoT stack: sensors and chips, networks, edge and mesh architectures, data use, user experience, and security and governance.
What Gartner’s 2018 forecast said
Gartner expected artificial intelligence to help organizations make IoT data more useful. Its 2018 forecast put the number of connected things at 14.2 billion in 2019 and 25 billion by 2021; those were projections made in 2018, not figures reported as actual counts. EE Times reproduced the estimates.
The other nine trends described capabilities and challenges Gartner expected to matter as IoT systems expanded. They are best read as connected parts of a technology landscape, rather than ten interchangeable products or a checklist that every organization had to adopt.
The ten strategic IoT trends
1. Artificial intelligence
Gartner’s first trend was using AI to extract more value from the growing volume of IoT data. Sensors can produce measurements, but those measurements become more useful when systems can analyze them and support decisions or automation. The forecast’s connected-things estimates framed the scale of the data challenge; they did not guarantee that organizations would have the data quality, infrastructure, or expertise to make every deployment effective.
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2. Infonomics and data broking
Infonomics treats information as an economic asset. In an IoT setting, data generated by connected devices could be valued, exchanged, or sold, creating potential business opportunities alongside questions about who may use it and under what terms. A dataset’s commercial value does not, by itself, settle ownership, permission, privacy, or liability.
3. IoT governance
Governance concerns the rules organizations use to create, store, use, share, retain, and delete IoT information. Those rules matter across the data lifecycle: collection practices affect what is captured, access rules shape who can use it, and retention and deletion policies determine how long it remains available. Governance is related to infonomics, but it is not the same thing: one considers data as an asset, while the other sets controls for handling it.
4. New wireless networking technologies
Gartner pointed to a widening set of connectivity options, including 5G, low-Earth-orbit satellites, and backscatter networks. The significance was not that one network would suit every IoT deployment; it was that organizations would need to choose among different trade-offs in endpoint cost, power use, bandwidth, and flexibility. The appropriate option depends on the application’s requirements and constraints.
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5. Novel IoT user experiences
IoT interaction would not always look like using a conventional screen and keyboard. Gartner expected sensors, algorithms, context, experience architectures, and socially aware interactions to shape how people and connected systems communicate. That makes the user experience a system-design concern: an interaction can depend on what a device senses and how software interprets the situation, not only on the device’s visible controls.
6. Sensor innovation
New sensors, lower prices, novel packaging, and improved algorithms were expected to broaden what IoT systems could detect. A sensor’s practical contribution therefore depends on more than its physical component: packaging and algorithms also affect how measurements can be collected and interpreted. The trend pointed to expanded sensing possibilities, not a guarantee that every new sensor would be accurate, affordable, or suitable for every deployment.
7. From intelligent edge to intelligent mesh
Gartner described a shift from designs centered on centralized cloud systems or individual edge devices toward a more dynamic mesh of connected things and services. In an edge-oriented design, processing is associated with devices or systems nearer to where data is generated; the mesh concept broadens the picture to interactions among connected things and services. The forecast described an architectural evolution, not a claim that edge computing would disappear or that every IoT system would use the same mesh design.
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8. Silicon chip innovation
Special-purpose chips were expected to reduce the power required for deep-neural-network workloads and make analytics or speech recognition possible in low-power endpoints. This connects chip design to both AI capability and device constraints: bringing computation closer to an endpoint can matter where power is limited. The trend was about enabling workloads in such settings, not a promise that every endpoint could run every AI task.
9. Social, legal, and ethical IoT
As IoT systems collect information and make inferences, questions arise about data ownership, privacy, algorithmic bias, and regulatory compliance. These are not separate from technical design: what a system collects and infers can affect people, while the rules that apply depend on the data and context. Gartner expected these social, legal, and ethical concerns to become increasingly important.
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10. Trusted hardware and operating systems
Gartner highlighted hardware and software combinations intended to improve trust and security, particularly where an organization cannot fully control the provenance of system components. Component provenance matters because trust depends in part on knowing what is in a device and what software it runs. Trusted hardware and operating systems address one part of the security problem; they do not remove the need for sound governance or other protections.
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How the trends fit together
The list spans different layers and organizational concerns. A useful way to interpret it is to ask which layer a trend affects, what capability it enables, and what constraints or risks accompany it.
- Endpoint: sensor innovation and specialized chips affect what a device can detect and process under power and cost constraints.
- Network: wireless options connect devices, with trade-offs among bandwidth, power use, endpoint cost, and flexibility.
- Edge and architecture: the move toward intelligent mesh concerns how connected things and services fit together, rather than only where data is processed.
- Data and business capability: AI, infonomics, and novel user experiences concern how data is analyzed, valued, and turned into useful interactions.
- Risk and control: governance, social and legal issues, and trusted hardware address rules, impacts, provenance, and security.
For an implementation decision, compare those dimensions with the project’s maturity and intended time horizon, then test them against practical limits such as interoperability, regulatory exposure, power, bandwidth, and cost. A promising capability is not automatically the right choice if its operating constraints or risks do not fit the deployment.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How to read the forecast today
The 2018 list’s five-year horizon ended in 2023, so it should be treated as a historical forecast rather than guidance about what will happen during 2026–2031. Gartner’s 2026 strategic-trends publication uses a new ten-item list; its items should not be substituted for the ten IoT trends discussed here. Gartner’s 2026 Hype Cycle for IoT has a separate purpose: evaluating innovations affecting IoT leaders and helping integrate IoT platforms with AI and digital-business initiatives. Gartner’s current framing says, “These 10 trends reflect how leading organizations are responding to complexity and opportunity in an AI-powered, hyperconnected world.”
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That newer framing is useful context, but it does not retroactively change what Gartner forecast in 2018. To assess the older list, keep its original 2018–2023 horizon in view and distinguish a prediction from evidence about what later occurred.
Is there one product that represents these trends?
No single product honestly represents all ten. A sensor kit or module, connectivity module or gateway, specialized chip, or security tool can illustrate one part of the landscape, but each covers only a subset of the forecast. The relevant choice depends on the deployment’s needs: what it must sense, how it will connect, where processing belongs, and what security and governance controls are required.
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